Predicting oxytocin binding dynamics in receptor genetic variants through computational modeling
Preeti Dubey1, Yingye Fang1, K Lionel Tukei1
1Department of Bioengineering, University of Washington, Seattle, WA, USA.
Abstract:
Approximately half of U.S. women giving birth annually receive Pitocin, a synthetic form of oxytocin (OXT), yet the optimal dosing remains challenging due to significant individual variability in response. To address this, we developed a mathematical model examining the effects of five OXT receptor (OXTR) variants (V45L, P108A, L206V, V281M, and E339K) on OXT-OXTR binding dynamics in human embryonic kidney cells (HEK293T) and myometrial smooth muscle cells. The model was parameterized using experimentally derived, cell-specific OXTR surface localization measurements and literature-reported OXT-OXTR-binding kinetics. The model revealed differences in time to equilibrium between HEK293T and myometrial cells, distinct dynamics among genetic variants, and that early increases in OXT could partially rescue diminished responses in V281M and E339K variants. This model provides key insights into how genetic variants influence OXT dose responses and offers a framework for tailoring OXT dosing to patient-specific genetic profiles.
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